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Agent Skill · 研究检索

orchestration(orchestration 搜索)

orchestration 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

orchestration 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 46,747。

总安装 766周安装 31GitHub Stars 10下载 241核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:orchestration(orchestration 搜索)
来源仓库:https://github.com/oakoss/agent-skills
仓库路径:skills/orchestration
安装命令:
npx skills add https://github.com/oakoss/agent-skills --skill orchestration
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/oakoss/agent-skills --skill orchestration

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

orchestration 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。

安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。适用于研究检索类 Agent 工作流,尤其关注工作流编排与调度场景。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/orchestration

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/oakoss/agent-skills --skill orchestration;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

orchestration 怎么安装?

在终端执行 npx skills add https://github.com/oakoss/agent-skills --skill orchestration。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

orchestration 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

orchestration 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

orchestration 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

orchestration 用的人多吗?

公开数据是累计安装 766 次,近一周安装 31 次,下载 241 次,GitHub 10 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

orchestration 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
orchestration

orchestration 搜索 · 本页

76610调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Orchestration

Overview

Coordinates skills, frameworks, and workflows across the project lifecycle. Combines pattern-based project classification with goal decomposition, hierarchical task planning, and multi-agent coordination.

Use this skill for project-level workflow decisions: which frameworks to activate, in what order, and how to validate progress between phases. For Claude Code-specific agent implementation details (agent configuration, batch sizing, prompt engineering), use the agent-patterns skill instead.

This skill does NOT replace project management tools. It provides the decision framework for sequencing capabilities and validating readiness at each transition point.

Quick Reference

NeedAction
Identify project typeClassify as Pattern A / B / C
Sequence frameworksFollow pattern-specific phase order
Decompose a goalExtract required effects, match capabilities
Validate readinessCheck phase-gate criteria before advancing
Find alternativesGenerate fallback capabilities per step
Score a planEvaluate cost, latency, risk, diversity
Coordinate agentsSelect orchestration pattern for task type
Pass contextUse context distillation for subagents

Pattern Identification

Classify every project before selecting frameworks or skills.

PatternCharacteristicsTimeline
A: Simple FeatureExisting system, well-understood, single-team1-5 days
B: New Product/SystemFrom scratch, security/compliance matters4-12 weeks
C: AI-Native/ComplexAI agents, RAG, knowledge graphs, orchestration8-20 weeks

Phase Gates

Do not advance without meeting gate criteria.

GateEntry Criteria
Design (Phase 2)PRP complete, problem validated, success metrics, user stories
Development (3)Architecture documented, data model designed, security threats mapped
Testing (Phase 4)Features complete, unit tests over 80%, code review, SAST clean
Deployment (5)All tests passing, UAT completed, security tested, coverage over 90%

Scoring Function

Plans are evaluated using weighted utility:

FactorWeightScores
Cost0.3free=1.0, low=0.8, medium=0.5, high=0.2
Risk0.3safe=1.0, low=0.8, medium=0.5, high=0.2
Latency0.2instant=1.0, fast=0.7, slow=0.3
Diversity0.2min(unique_domains / 5, 1.0)

Modifiers: recently used (within 3 steps) gets -30% penalty; novel capability gets +20% bonus.

Multi-Agent Orchestration Patterns

PatternUse Case
HierarchicalParent delegates to specialized subagents
SequentialChain of experts (architect -> dev -> review)
ParallelIndependent tasks running simultaneously
HandoffOne agent passes context to the next

Key rules: max delegation depth of 3, use context distillation (not full codebase), log all agent interactions.

MCP Integration

MCP (Model Context Protocol) standardizes how agents connect to external tools, data sources, and prompt templates. The orchestrator discovers available MCP servers at startup and routes tool calls from subagents to the correct server.

MCP PrimitiveRole in Orchestration
ResourcesDiscover available data (schemas, configs, docs) before work
ToolsExecute validated actions with typed arguments
PromptsReuse domain-specific instruction templates across agents
SamplingAllow servers to request AI reasoning mid-execution

Common Mistakes

MistakeCorrect Pattern
Treating all projects as Pattern A (simple feature)Classify first: Pattern A (simple), B (new product), C (AI-native) before selecting frameworks
Skipping phase gates to move fasterEnforce gate criteria before advancing; skipping causes compounding rework
Activating all available skills simultaneouslyLimit to 1-3 skills per phase with clear deliverables and handoffs
No decision logging for capability choicesLog rationale, alternatives considered, scores, and rejection reasons at each step
Building HTN plans without validating preconditionsCheck project state (files, dependencies, env vars) against each capability's requirements first
Delegating without a clear objective manifestEvery subagent needs an objective, constraints, max tokens, and available tools
Passing entire codebase to subagentsUse context distillation to pass only relevant symbols and facts

Delegation

  • Discover project pattern and classify scope: Use Explore agent to survey the codebase, dependencies, and requirements
  • Execute multi-phase orchestration plan: Use Task agent to implement phase-specific deliverables with gate validation
  • Design architecture and capability sequences: Use Plan agent to decompose goals and build scored HTN plans

References

  • goal-decomposition.md -- HTN planning, goal analysis, capability matching, precondition validation, scoring, decision logging
  • project-patterns.md -- Pattern A/B/C classification, phase sequences, skill coordination by phase, parallelization
  • multi-agent-coordination.md -- Hierarchical, sequential, parallel orchestration patterns, delegation manifests, recursion limits
  • mcp-orchestration.md -- MCP architecture, resources, tools, prompts, multi-server orchestration, bidirectional sampling
  • context-distillation.md -- Symbol indexing, fact extraction, recursive context reduction, token management
  • error-handling.md -- Objective drift, tool failure, context overflow, circuit breakers, recovery strategies, logging

平台分布

Codex

36.16%
按下载量换算87

Claude

29.58%
按下载量换算71

Cursor

20.86%
按下载量换算50

Gemini CLI

9.88%
按下载量换算24

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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